Question Answering over Text and Knowledge Base

208 Pages·2022·8.279 MB·English

by  Saeedeh Momtazi, Zahra Abbasiantaeb

Saeedeh Momtazi 
Zahra Abbasiantaeb
Question
Answering
over Text and
Knowledge Base
Question Answering over Text and Knowledge
Base
Saeedeh Momtazi • Zahra Abbasiantaeb
Question
Answering
over Text and
Knowledge Base
SaeedehMomtazi ZahraAbbasiantaeb
ComputerEngineeringDepartment ComputerEngineeringDepartment
AmirkabirUniversityofTechnology AmirkabirUniversityofTechnology
Teheran,Iran Teheran,Iran
ISBN978-3-031-16551-1 ISBN978-3-031-16552-8 (eBook)
https://doi.org/10.1007/978-3-031-16552-8
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To ourfamilies
Preface
The advance of natural language processing and information retrieval models has
significantlyinfluencedthefieldofquestionansweringsystems.Therehavebeenan
increasedattention and researchon questionansweringsystems. By the adventof
renownquestionansweringsystemslikeSiriandGoogleAssistant,theimportance
ofthequestionansweringsysteminthiseraisevident.
Theimportanceofquestionansweringsystemsinthefieldsofnaturallanguage
processing and information retrieval, existence of a large number of scientific
papers,and advancesin this field frombasic informationretrievalmodelsto deep
neural networks convinced us to write this book. Moreover, the available survey
papersonquestionansweringsystemsarenotcomprehensive,andtheyonlycover
the studies on one type of question answering systems. As a result, they are
not enough for obtaining a big picture of question answering systems advances
and categories. Hence, publishinga specific and comprehensivebook on question
answering systems that can be used by researchers starting in this field seems
necessary.Such a bookcan helpthe readersto followthe state-of-the-artresearch
byprovidingessentialandbasicknowledge.
Consequently,wehavesensedtheneedtopublishabookonquestionanswering
systems and started writing this book. Both authors of the book have several
yearsofexperienceandresearchonquestionansweringsystems.SaeedehMomtazi
completedher PhD dissertation on questionansweringsystems, andafter that she
ranacoupleoftutorialsonthefieldandlateronasanassociateprofessorsupervised
differentprojectson question answering.Zahra Abbasiantaebcompletedher MSc
onquestionansweringsystemsandfollowedthistopicthroughpublishingsurveys
andtechnicalpapers.
vii
viii Preface
In summary, we have done our best to convey the big picture to the readers
andalso coverasmuchdetailas possible essentialforfollowingthe latest papers.
Wehavestudiedthequestionansweringsystemsinthreemaincategoriesbasedon
the source of the data that can be unstructuredtext, structured knowledge graphs,
or a combination of both. In addition, we provided the required materials for
understandingthetechnicalchaptersandreviewedmodelsinthebook.
Tehran,Iran SaeedehMomtazi
May2022 ZahraAbbasiantaeb
Acknowledgements
No worthwhile work was ever completed in isolation. Finishing this book could
nothavebeenpossiblewithoutthehelpofseveralpeople.We owethema debtof
gratitudeforalltheirsupportandkindness.
Firstofall,ourappreciationgoestoRalfGerstner,executiveeditorforComputer
ScienceatSpringer,forallhishelpandsupportduringwritingandrevisionofthe
proposalandthebook.
We are very grateful to the Computer Engineering Department of Amirkabir
University of Technology for providing a pleasant work environment, where we
coulddevoteasubstantialamountoftimetowritingthisbook.
WeareverythankfulforProf.Dr.DietrichKlakowandProf.Dr.FelixNaumann
who had substantial influence in our research journey on question answering
systemsandeducation.
Last but not least, appreciation goes to our families for their true love. Their
unconditional support and care were the best help. We are grateful for all their
patienceandtoleranceindifficultconditions.
ix
Contents
1 Introduction .................................................................. 1
1.1 Introduction ............................................................. 1
1.2 BookOverview ......................................................... 3
References .................................................................... 5
2 HistoryandArchitecture.................................................... 9
2.1 Introduction ............................................................. 9
2.2 Closed-DomainSystemswithStructuredData ....................... 10
2.3 Open-DomainSystemswithUnstructuredData ...................... 11
2.3.1 QAatTREC .................................................... 12
2.3.2 ArchitectureofTextQA ........................................ 13
2.4 Open-DomainSystemswithStructuredData ......................... 18
2.4.1 ArchitectureofQAoverKnowledgeGraph .................. 20
2.5 HybridSystems ......................................................... 23
2.5.1 ArchitectureofHybridQA .................................... 24
2.6 Summary ................................................................ 25
References .................................................................... 25
3 QuestionAnsweringEvaluation............................................ 29
3.1 EvaluationofTextQA .................................................. 29
3.1.1 Datasets ......................................................... 29
3.1.2 Metrics .......................................................... 33
3.2 EvaluationofKBQA ................................................... 35
3.2.1 KnowledgeGraphs ............................................. 35
3.2.2 Datasets ......................................................... 41
3.2.3 Metrics .......................................................... 44
3.3 Summary ................................................................ 46
References .................................................................... 46
xi
xii Contents
4 IntroductiontoNeuralNetworks .......................................... 49
4.1 NeuralArchitectures ................................................... 49
4.1.1 Feed-ForwardNeuralNetwork ................................ 51
4.1.2 ConvolutionalNeuralNetwork(CNN) ....................... 52
4.1.3 RecurrentNeuralNetwork(RNN) ............................ 53
4.2 DistributedWordRepresentation ...................................... 56
4.2.1 Word2Vec ...................................................... 56
4.2.2 GloVe ........................................................... 58
4.3 ContextualWordEmbedding .......................................... 60
4.3.1 ELMo ........................................................... 61
4.3.2 BERT ........................................................... 62
4.3.3 RoBERTa ....................................................... 65
4.4 Summary ................................................................ 65
References .................................................................... 66
5 QuestionAnsweringoverText.............................................. 67
5.1 Introduction ............................................................. 67
5.2 Non-deepLearning-BasedModels .................................... 68
5.3 DeepLearning-BasedModels ......................................... 73
5.3.1 Representation-BasedModels ................................. 73
5.3.2 Interaction-BasedModels ..................................... 80
5.3.3 HybridModels ................................................. 94
5.4 Summary ................................................................ 115
References .................................................................... 115
6 QuestionAnsweringoverKnowledgeBase ............................... 119
6.1 Introduction ............................................................. 119
6.2 TraditionalModels ..................................................... 119
6.3 SimpleQuestionsoverKB ............................................. 127
6.4 ComplexQuestionsoverKB .......................................... 141
6.5 Summary ................................................................ 155
References .................................................................... 155
7 KBQAEnhancedwithTextualData....................................... 157
7.1 Introduction ............................................................. 157
7.2 StudyofModels ........................................................ 157
7.3 Summary ................................................................ 181
References .................................................................... 181
8 QuestionAnsweringinRealApplications................................. 185
8.1 IBMWatson ............................................................ 185
8.1.1 TheJeopardy!Challenge ...................................... 185
8.1.2 DeepQA ........................................................ 188
8.1.3 Baselines ........................................................ 193
8.2 DrQA .................................................................... 194